Dataset Information

CYP19A1 fine-mapping and Mendelian randomization: estradiol is causal for endometrial cancer.

ABSTRACT: Candidate gene studies have reported CYP19A1 variants to be associated with endometrial cancer and with estradiol (E2) concentrations. We analyzed 2937 single nucleotide polymorphisms (SNPs) in 6608 endometrial cancer cases and 37?925 controls and report the first genome wide-significant association between endometrial cancer and a CYP19A1 SNP (rs727479 in intron 2, P=4.8×10(-11)). SNP rs727479 was also among those most strongly associated with circulating E2 concentrations in 2767 post-menopausal controls (P=7.4×10(-8)). The observed endometrial cancer odds ratio per rs727479 A-allele (1.15, CI=1.11-1.21) is compatible with that predicted by the observed effect on E2 concentrations (1.09, CI=1.03-1.21), consistent with the hypothesis that endometrial cancer risk is driven by E2. From 28 candidate-causal SNPs, 12 co-located with three putative gene-regulatory elements and their risk alleles associated with higher CYP19A1 expression in bioinformatical analyses. For both phenotypes, the associations with rs727479 were stronger among women with a higher BMI (Pinteraction=0.034 and 0.066 respectively), suggesting a biologically plausible gene-environment interaction.

SUBMITTER: Thompson DJ

PROVIDER: S-EPMC4697192 | biostudies-literature | 2016 Feb

REPOSITORIES: biostudies-literature

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CYP19A1 fine-mapping and Mendelian randomization: estradiol is causal for endometrial cancer.

Thompson Deborah J DJ O'Mara Tracy A TA Glubb Dylan M DM Painter Jodie N JN Cheng Timothy T Folkerd Elizabeth E Doody Deborah D Dennis Joe J Webb Penelope M PM Gorman Maggie M Martin Lynn L Hodgson Shirley S Michailidou Kyriaki K Tyrer Jonathan P JP Maranian Mel J MJ Hall Per P Czene Kamila K Darabi Hatef H Li Jingmei J Fasching Peter A PA Hein Alexander A Beckmann Matthias W MW Ekici Arif B AB Dörk Thilo T Hillemanns Peter P Dürst Matthias M Runnebaum Ingo I Zhao Hui H Depreeuw Jeroen J Schrauwen Stefanie S Amant Frederic F Goode Ellen L EL Fridley Brooke L BL Dowdy Sean C SC Winham Stacey J SJ Salvesen Helga B HB Trovik Jone J Njolstad Tormund S TS Werner Henrica M J HM Ashton Katie K Proietto Tony T Otton Geoffrey G Carvajal-Carmona Luis L Tham Emma E Liu Tao T Mints Miriam M Scott Rodney J RJ McEvoy Mark M Attia John J Holliday Elizabeth G EG Montgomery Grant W GW Martin Nicholas G NG Nyholt Dale R DR Henders Anjali K AK Hopper John L JL Traficante Nadia N Ruebner Matthias M Swerdlow Anthony J AJ Burwinkel Barbara B Brenner Hermann H Meindl Alfons A Brauch Hiltrud H Lindblom Annika A Lambrechts Diether D Chang-Claude Jenny J Couch Fergus J FJ Giles Graham G GG Kristensen Vessela N VN Cox Angela A Bolla Manjeet K MK Wang Qin Q Bojesen Stig E SE Shah Mitul M Luben Robert R Khaw Kay-Tee KT Pharoah Paul D P PD Dunning Alison M AM Tomlinson Ian I Dowsett Mitch M Easton Douglas F DF Spurdle Amanda B AB

Endocrine-related cancer 20151116 2

Candidate gene studies have reported CYP19A1 variants to be associated with endometrial cancer and with estradiol (E2) concentrations. We analyzed 2937 single nucleotide polymorphisms (SNPs) in 6608 endometrial cancer cases and 37 925 controls and report the first genome wide-significant association between endometrial cancer and a CYP19A1 SNP (rs727479 in intron 2, P=4.8×10(-11)). SNP rs727479 was also among those most strongly associated with circulating E2 concentrations in 2767 post-menopaus ...[more]

PMID: 26574572

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Project description:ObjectiveThis study aimed to investigate the causal associations between several liver traits (liver iron content, percent liver fat, alanine transaminase levels, and liver volume) and colorectal cancer (CRC) risk using a Mendelian randomization (MR) approach to improve our understanding of the disease and its management.MethodsGenetic variants were used as instrumental variables, extracted from genome-wide association studies (GWAS) datasets of liver traits and CRC. The Two-Sample MR package in R was used to conduct inverse variance weighted (IVW), MR Egger, Maximum likelihood, Weighted median, and Inverse variance weighted (multiplicative random effects) MR approaches to generate overall estimates of the effect. MR analysis was conducted with Benjamini-Hochberg method-corrected P values to account for multiple testing (P < 0.013). MR-PRESSO was used to identify and remove outlier genetic variants in Mendelian randomization (MR) analysis. The MR Steiger test was used to assess the validity of the assumption that exposure causes outcomes. Leave-one-out validation, pleiotropy, and heterogeneity testing were also conducted to ensure the reliability of the results. Multivariable MR was utilized for validation of our findings using the IVW method while also adjusting for potential confounding or pleiotropy bias.ResultsThe MR analysis suggested a causal effect between liver volume and a reduced risk of CRC (OR 0.60; 95% CI, 0.44-0.82; P = 0.0010) but did not provide evidence for causal effects of liver iron content, percent liver fat, or liver alanine transaminase levels. The MR-PRESSO method did not identify any outliers, and the MR Steiger test confirmed that the causal direction of the analysis results was correct in the Mendelian randomization analysis. MR results were consistent with heterogeneity and pleiotropy analyses, and leave-one-out analysis demonstrated the overall values obtained were consistent with estimates obtained when all available SNPs were included in the analysis. Multivariable MR was utilized for validation of our findings using the IVW method while also adjusting for potential confounding or pleiotropy bias.ConclusionThe study provides tentative evidence for a causal role of liver volume in CRC, while genetically predicted levels of liver iron content, percent liver fat, and liver alanine transaminase levels were not associated with CRC risk. The findings may inform the development of targeted therapeutic interventions for colorectal liver metastasis (CRLM) patients, and the study highlights the importance of MR as a powerful epidemiological tool for investigating causal associations between exposures and outcomes.

Dataset Information

CYP19A1 fine-mapping and Mendelian randomization: estradiol is causal for endometrial cancer.

Publications

CYP19A1 fine-mapping and Mendelian randomization: estradiol is causal for endometrial cancer.

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